Data proliferation refers to the unprecedented amount of data, for example, structured and unstructured data, that, e.g., business and government continue to generate at an unprecedented rate. Additionally, data proliferation refers to the usability problems that result from attempting to store and manage that data. While originally pertaining to problems associated with paper documentation, data proliferation has become a major problem in primary and secondary data storage on computers.
While digital storage has become cheaper, the associated costs, from, for example, raw power to maintenance and from metadata to search engines, have not kept up with the proliferation of data. Although the power required to maintain a unit of data has fallen, the cost of facilities that house the digital storage has tended to rise.
Data proliferation may be problematic for several reasons. For example, data proliferation may cause difficulty when trying to find and retrieve information. An organization's employees can spend more than one hour per week to find, for example, hard-copy documents, which increases costs to manage and store such documents. In networks of primary and secondary data storage, problems finding electronic data are analogous to problems finding hard copy data. Additionally, for example, data proliferation may cause data loss and legal liability when data is disorganized, not properly replicated and/or cannot be found in a timely manner. Moreover, data proliferation may increase manpower requirements to manage, for example, increasingly chaotic data storage resources. Furthermore, data proliferation may cause slower networks and application performance due to excess traffic as users search and search again for the material they need. Data proliferation may also cause high cost in terms of the energy resources required to operate storage hardware.
Data centers, e.g., shared data centers, may be used for data storage, amongst other purposes. For example, an organization may obtain data storage from, e.g., a data storage service provider. In obtaining such data storage, an organization must determine an amount of storage necessary to meet their data storage requirements. However, such a determination of necessary storage information may be difficult and/or expensive to perform. As a result, an organization may obtain more storage than necessary for their actual storage requirements, which increases expenditures and reduces efficiencies.
Moreover, a more efficient approach to data storage management is needed. That is, for example, with the demands of line of business (LOB) owners for faster provisioning, application owners designing their own solutions, the desire for information technology (IT) to be more energy efficient, storage growth that continues despite efforts to optimize storage, the desire for visibility to storage cost and usage ownership, a desire to control IT costs and/or business requesting storage multi-years in advance, e.g., due to slow cycle of past procurement, the current approaches to data storage provisioning and management are insufficient.
Accordingly, there exists a need in the art to overcome the deficiencies and limitations described herein above.